1. Field of the Invention
The present invention relates generally to digital communication techniques, and more particularly, to an apparatus for and method of developing equalized values from samples of a signal received from a channel.
2. Description of the Background of the Invention
Discrete data transmission is the transmission of messages from a transmitter to a receiver through a communication channel. A message sender or sending device, located at the transmitter, communicates with a message receiver by selecting a message and sending a corresponding signal or waveform that represents this message through the communication channel. The receiver determines the message sent by observing the channel output. Successive transmission of discrete data messages is known as digital communication. Channel noise often interferes with the transmission and degrades the transmitted message and leads to some uncertainty as to the content of the original message at the receiver. The receiver uses a procedure known as detection to decide which message, or sequence of messages, the sender transmitted. Optimum detection minimizes the probability of an erroneous receiver decision on which message was transmitted.
Messages are comprised of digital sequences of bits converted into electrical signals that are sent through the channel. These bits are typically encoded prior to modulation. Encoding is the process of converting the messages from an innate form, typically bits, into values that represent the messages. Modulation is a procedure for converting the values into analog signals for transmission through the channel. The channel distorts the transmitted signals both deterministically and with random noise. Those conditions that interfere with proper reception include additive white Gaussian noise (AWGN) and coherent noise, frequency dependent channel distortion, time dependent channel distortion, and fading multipath. Because of these effects, there is some probability that the sent message is corrupted when it reaches the receiver.
Upon reception, the receiver demodulates the incoming waveform. In general, demodulation attempts to recover the original transmitted signals as accurately as possible and converts the recovered signals to estimates of the values. There are several steps to this process, including downmixing the radio frequency (RF) and near-baseband intermediate frequency (IF) signals to the baseband representation, channel equalization, and decoding. Symbol and carrier recovery are undertaken so that the discrete time samples are at the correct symbol rate and the signal is moved exactly down to baseband. The receiver employs a detector to probabilistically determine the value estimates. It is important that the methods of demodulating and detecting the received signal as employed by the receiver consider both the possible transmitted values and potential for channel-induced errors. The value estimates are then decoded by converting the value estimates back into the innate form of the message.
Digital communications systems receive the transmitted information by periodically sampling the output of the demodulator once per symbol interval. This requires the receiver design to overcome the problems associated with system synchronization, as related to symbol-timing and carrier recovery, under non-ideal transmission channel conditions. The optimal times for the receiver to sample the received signal are generally unknown due to the propagation delay from the transmitter to the receiver and the influence of channel conditions such as multipath. The propagation delay in the transmitted signal also results in a carrier phase offset. For those transmission systems requiring a receiver to employ a phase-coherent detector, the receiver develops an estimate of the propagation delay and derives an estimate of the transmitted symbol timing and phase error directly from the received signal. The exception to this is the case where pilot or control signals are embedded in the transmitted signal. In such a case, the receiver uses the embedded pilot or control signal to synchronize the receiver to the transmitter. In either case, the receiver overcomes the system synchronization obstacles by performing three basic functions: carrier recovery, timing recovery, and channel equalization.
As noted above, the carrier recovery process includes a number of steps whereby the received radio frequency (RF) signal is demodulated. In part, the near-baseband signal is demodulated so as to recover the information-bearing baseband signal and to remove any residual carrier phase offset. This final step is often referred to as phase-locking.
The timing recovery process is used to recover the transmitter time base and synchronize the receiver and transmitter clocks. Once achieved, this synchronization permits the receiver to sample the received signal at optimum points in time and reduce slicing errors.
The channel equalization process attempts to compensate for the imperfections within the transmission channel, which change the amplitude and phase of the received signal as it traverses the channel. These imperfections are generally frequency dependent, time dependent, and dynamic. Because of this, it is advantageous to employ an adaptive equalizer filter system to remove the amplitude and phase distortions from the channel.
There are a number of phase-locked loop (PLL) techniques in existence. A limited list of example approaches that will be appreciated by those skilled in the art, are Costas loops, squaring loops, and, more generally, decision directed and non-decision directed loops.
Phase-locking mechanisms typically involve three common elements. They are phase error detection/generation, phase error processing, and local phase reconstruction. The phase error detection operation, as implemented by a phase detector, derives a phase difference measurement between the transmitted signal phase, as detected at the receiver, and a phase estimate of the incoming signal as developed by the receiver. The phase error measurement is the difference between the phase of the received and the actual transmitted signal.
The phase error processing operation, commonly embodied by an integrator or low-pass loop filter, extracts the essential phase difference trends by averaging, over a period of time or within a time window, the magnitude of the phase error. Properly designed, the phase error processing operation rejects random noise and other undesirable components of the phase error signal. In order to insure stability, the loop filter absorbs gain resident in the phase detector. There are analog, digital and hybrid analog-digital phase error detection methods utilized within phase-locked loops. These methods use components including, but not limited to, modulo-2π phase detectors, binary phase detectors, phase-splitting filters, and maximum-likelihood carrier phase estimators.
The local phase reconstruction operation is responsible for controlling the generation and phase of a local oscillator. The local oscillator is used to demodulate the near-baseband signal with a locally generated oscillator frequency having the same frequency and phase as the near-baseband signal. When locked, the resulting local oscillator signal has the same frequency and phase characteristics as the signal being demodulated to baseband. The local oscillator may be implemented using either analog or digital means. Various types of voltage controlled crystal oscillators and numerically controlled oscillators, VCXO's and NCO'S, respectively, may be used to regenerate the local carrier.
In the case of an analog circuit, the local phase reconstruction operation is implemented using a voltage-controlled oscillator. The VCXO uses the processed phase error information to regenerate the local phase of the incoming signal by forcing the phase error to zero.
Any phase-locking mechanism has some finite delay in practice so that the mechanism attempts to predict the incoming phase and then measures the accuracy of that prediction in the form of a new phase error. The more quickly the phase-lock mechanism tracks deviations in phase, the more susceptible the mechanism is to random noise and other imperfections. This is all the more the case where the received signal exists in a strong multipath environment. Thus, an appropriate trade-off is made between these two competing effects when designing a synchronization system.
Timing recovery, or synchronization, is the process whereby a receiver synchronizes the local time base thereof to the transmitter symbol rate. This allows for precise sampling time instants during the symbol period so as to maximize the likelihood of correctly determining the value of the transmitted symbol. As previously described, the PLL subsystem is insufficient to recover the symbol rate. Instead, a separate symbol-timing recovery function is added in combination with the PLL to provide timing recovery. Improper symbol-timing recovery is one source of intersymbol interference (ISI) and significantly degrades the performance of the receiver.
As those skilled in the art will appreciate, proper sampling of the demodulator output is directly dependent upon proper timing recovery. There are a number of methods utilized by systems to perform local clock recovery. In a first system, various types of clocking signals are encoded into the bit stream. In a second system, no predefined synchronization symbols are transmitted and only data are sent and the locked local clock is derived from the received data stream. It should be noted that the latter system appears to be more prevalent due to the desire for bandwidth efficiency.
In addition, timing recovery methods are also distinguishable as to their use of the decision device output of the receiver. A non-decision aided methodology does not depend upon the output of the decision device. An example of such a methodology is the square-law timing recovery method. Also, envelope-timing recovery is an equivalent square-law timing recovery method utilized in a Quadrature Amplitude Modulation (QAM) receiver.
Decision directed (also known as decision-aided) timing recovery uses the decision device output. One example of a decision directed timing recovery method minimizes the mean-square error, over the sampling time phase, between the output of either a linear equalizer (LE) or a decision feedback equalizer (DFE) and the decision device output.
The decision device is responsible for assigning a symbol value to each sample obtained from the demodulator. There are both hard and soft decision devices. An example of a hard decision device is a decision slicer or a Viterbi decoder. In the case of decision directed timing recovery methods, care is taken to ensure that there is not excessive delay between the decision device output and the input sampling function. Excessive delay degrades the overall performance of the receiver or, in the worst-case, causes the phase-locked loop to become unstable. As will be appreciated by those skilled in the art, the quality of the symbol-timing estimates is dependent upon the overall signal-to-noise ratio (SNR) and is a function of the signal pulse shape and the channel characteristics.
There are numerous sources of channel distortion and interference that may result in poor receiver performance, as measured by either bit error rate (BER) or overall data transfer rates of a receiver design. Factors include noise, AWGN, inter-symbol interference (ISI) and multipath conditions.
Receivers also compensate for channels having significant multipath characteristics. There are various means of classifying or describing multipath phenomenon, depending upon the channel frequency response and time varying multipath effects. Four common categorizations, familiar to those skilled in the art, are slow changing frequency non-selective fading, fast changing frequency-non selective fading, slow changing frequency selective fading, and fast changing frequency selective fading.
Typically, multipath is the result of the transmitted signal arriving at the receiver via different transmission paths, each having a unique composite propagation time to the receiver. The multipath induced ISI results in the receiver contending with non-constant amplitude and non-linear phase response of the channel. The second effect is referred to as fading. Fading is due to the propagation delay associated with each propagation path resulting in constructive and destructive interference at the receiver. Fading causes degradation of SNR.
This simplistic description is further refined into four categories, familiar to those skilled in the art, as summarized by the practical implications thereof. In practice, a channel exhibiting slowly changing, frequency non-selective fading means that all of the propagation paths are received within one symbol period and that the channel equally affects all the signal frequency components. This is considered the most easily compensated fading channel phenomenon. Fast changing, frequency non-selective fading arises where the channel varies during the symbol period. Fast fading is very difficult to compensate effectively.
A channel may be characterized as having slow, frequency-selective multipath when the channel distorts the received symbol in the frequency domain and not all the frequency components are equally affected. As a consequence, the baseband pulse shape is distorted and intersymbol interference results. Finally, fast changing, frequency-selective fading is considered the worst-case type of channel, and results when the received symbol is spread over many symbol periods and the channel characteristics also vary during the symbol period.
Fading is also roughly divided into large- and small-scale fading categories as shown in FIG. 1. Large motions of the receiver, such as occur in mobile applications, cause large-scale fading, whereas small-scale fading is due to motion of the receiver. Large-scale fading is also called log-normal fading, because the amplitude thereof has a log-normal probability density function. Small-scale fading is usually described as Rayleigh- or Ricean-fading, depending on which probability distribution function (pdf) best describes it. In addition, a Nakagami-m distribution has also been used to characterize some multipath channel conditions.
Many modern digital communications systems employ adaptive equalization to compensate for the effects of changing conditions and disturbances in the signal transmission channel. Equalization is used to remove the baseband inter-symbol interference caused by transmission channel distortion and may be performed on baseband or passband signals. Equalization is often performed on the near-baseband signal prior to carrier recovery and the down mixing to produce a baseband signal. This is particularly the case in a decision directed carrier recovery process, as will be appreciated by those skilled in the art, which requires at least a partially open eye.
A representation of an 8-VSB, vestigial sideband, eye diagram is shown in FIG. 2. The eye diagram is the overlay of many traces of the received RF signal amplitude at the instant of sampling. The convergence of the many signal traces forms seven “eyes” that coincide with the occurrence of clock pulses in the receiver. At each sampling time, the demodulated RF amplitude assumes one of eight possible levels. If the 8-VSB signal is corrupted during transmission, these “eyes” will close up and disappear, as the RF signal will no longer possess the correct amplitude at the right instant.
An adaptive equalizer filter system is essentially an adaptive digital filter having a modifiable frequency and phase response that compensates for channel distortions. As will be appreciated by those skilled in the art, several architectures, methods and algorithms are available to implement this function. In one embodiment, a feed-forward equalizer (FFE) develops a partially equalized signal that is provided to a decision feedback equalizer (DFE). In typical systems of this type, the FFE is responsible for minimizing or eliminating ghosts resulting from precursor inter-symbol interference (ISI) while the DFE is responsible for minimizing or eliminating ghosts resulting from postcursor ISI. In another system, the FFE reduces or eliminates ghosts due to precursor and some postcursor ISI while the DFE reduces or eliminates ghosts resulting from postcursor ISI.
The impact on receiver performance of multipath induced ISI is reduced by the application of channel estimation and equalization. The effectiveness of the channel estimate has a direct relationship to elimination of ISI. An ideal channel estimate, in theory, would allow complete removal of the ISI. Obtaining an ideal channel estimate, however, is problematic when presented with particularly odious channel characteristics.
Another approach to improving performance in the presence of multipath interference is based on the diversity principle. The different propagation paths are used in combination to mitigate the multipath fading. This is possible because the propagation paths are usually not correlated, meaning it is unlikely that all of them fade simultaneously. The diversity concept models the channel fading mechanism as a channel burst error. Thus, providing temporally or frequency-based redundant copies of the transmitted information improves the likelihood of successful data transmission.
Diversity techniques include temporal diversity and frequency diversity. Frequency diversity requires that the same information be transmitted over a number of carriers where the spacing of successive carriers equals or exceeds the coherent bandwidth of the information channel. Temporal diversity employs the use of a number (L) of independently fading versions of the same information-bearing signal transmitted into L different time slots, where the separation between successive time slots equals or exceeds the coherence time of the channel. Thus, L copies of the transmitted information are presented to the receiver at varying times based on the transmission path.
One realization of this concept is a Rake Receiver. The Rake Receiver exploits the multipath phenomenon to improve system performance. Multiple baseband correlators are used to individually process multiple multipath components. The correlator outputs are then added to increase total signal strength.
The above characterizations are intended only as a partial, non-limiting list of example techniques that may be employed and are not intended in any way to represent any limitation upon the disclosed invention.
Despite the numerous techniques available in the present state of the art, receivers exhibit significant performance degradation in the presence of strong multipath environments. This is particularly true in the case of terrestrial digital broadcasting systems. In particular, the present state of the art receiver using an equalizer typically uses subtractive methods to remove interfering multipath signals. This has a distinct disadvantage in a changing multipath fading environment. In particular, these receiver systems attempt to identify and lock onto the single strongest received signal coming through a given transmission path or channel. This is accomplished at start up of the equalizer by establishing a tap of unity magnitude at a center point of the FFE. Upon reception, signals corresponding to other transmission paths are subtractively removed from the incoming total signal. This effectively removes all diversity from the receiving process (if diversity is used in the system). Also, the receiver can lose lock as the strength of the primary multipath signal fades or a new stronger signal appears. This introduces significant carrier phase offset at the receiver. Changing multipath conditions thus often necessitate a receiver to reacquire carrier lock, resulting in a possibly noticeable disruption in information flow to a user at the receiver.